A New Time Series Forecasting Model Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Temporal Convolutional Network

In this paper, a new hybrid time series forecasting model based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a temporal convolutional network (TCN) (CEEMDAN-TCN) is proposed. The CEEMDAN is used to decompose the time series data and the TCN is used to obtai...

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Detalles Bibliográficos
Autores principales: Guo, Chen, Kang, Xumin, Xiong, Jianping, Wu, Jianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542464/
https://www.ncbi.nlm.nih.gov/pubmed/36248248
http://dx.doi.org/10.1007/s11063-022-11046-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542464/
https://www.ncbi.nlm.nih.gov/pubmed/36248248
http://dx.doi.org/10.1007/s11063-022-11046-7

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